benchmark_evaluator.py
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#!/usr/bin/env python3
"""Benchmark 评估器 - create-drama 技能"""
import json
import sys
import re
def evaluate(result_json, benchmark_file, testdata_dir):
"""评估剧本生成结果"""
try:
result = json.loads(result_json)
except:
return {
"score": 50,
"dimensions": {},
"reason": "无法解析输出JSON"
}
scores = {}
# D1: 素材分析准确性 (20%)
# 检查是否识别素材类型、提取核心元素、语言检测、风格适配
name = result.get('name', '')
title = result.get('title', '')
description = result.get('description', '')
language = result.get('language', 'zh')
# 核心元素评估
d1_score = 0
# 角色和冲突提取 - 检查剧本是否有角色和台词(代表有故事)
characters = result.get('characters', [])
script = result.get('script', [])
if len(characters) >= 2:
d1_score += 25
if len(script) >= 5:
d1_score += 25
# 语言检测 - 中文字符 vs 英文字符
has_cn = any('\u4e00' <= c <= '\u9fff' for c in (name + title + description))
if (language == 'zh' and has_cn) or (language == 'en' and not has_cn):
d1_score += 25
elif language in ['zh', 'en', 'multi']:
d1_score += 15
# 风格适配检测
description_len = len(description)
if description_len >= 10:
d1_score += 25
scores['D1'] = min(100, d1_score)
# D2: 角色配置合理性 (20%)
# 角色数量(2-5)、音色匹配、站位配置
d2_score = 0
char_count = len(characters)
if 2 <= char_count <= 5:
d2_score += 40
elif char_count > 5:
d2_score += 20
# 音色匹配检查
valid_voices = ['zh_male_m191', 'zh_female_cancan', 'zh_male_shaonianzixin',
'zh_female_sajiaoxuemei', 'zh_male_dayi', 'zh_male_sunwukong',
'en_male_tim', 'en_female_dacey', 'en_female_stokie']
voice_match = 0
for char in characters:
voice = char.get('voiceId', '')
if any(v in voice for v in valid_voices):
voice_match += 1
if char_count > 0:
voice_ratio = voice_match / char_count
d2_score += int(60 * voice_ratio)
scores['D2'] = min(100, d2_score)
# D3: 剧本结构完整性 (20%)
# Classic 结构(开场2→铺垫4→冲突6→反转4→结局2)、台词数量(10-20)、台词≤30字
d3_score = 0
# 台词数量
script_count = len(script)
if 10 <= script_count <= 20:
d3_score += 30
elif 5 <= script_count < 10:
d3_score += 20
elif script_count > 0:
d3_score += 10
# 台词长度检查
long_lines = 0
for line in script:
dialogue = line.get('dialogue', '')
if len(dialogue) > 30:
long_lines += 1
long_ratio = long_lines / script_count if script_count > 0 else 1
if long_ratio < 0.2:
d3_score += 30
elif long_ratio < 0.5:
d3_score += 20
else:
d3_score += 10
# 结构完整性 - 检查是否有 position 字段
has_position = any('position' in line for line in script)
if has_position:
d3_score += 40
else:
d3_score += 20
scores['D3'] = min(100, d3_score)
# D4: 图片生成质量 (20%)
# 立绘 prompt 含空白脸部、背景图/封面图 prompt
d4_score = 0
# 检查空白脸部
blank_face_count = 0
for char in characters:
prompt = char.get('imagePrompt', '')
if '空白' in prompt or '不要画' in prompt or '纯肉色' in prompt or 'blank' in prompt.lower():
blank_face_count += 1
if char_count > 0:
blank_ratio = blank_face_count / char_count
if blank_ratio >= 0.8:
d4_score += 60
elif blank_ratio >= 0.5:
d4_score += 40
elif blank_ratio > 0:
d4_score += 20
# 背景图
background_prompt = result.get('backgroundPrompt', '')
if background_prompt:
d4_score += 20
else:
d4_score += 10
# 封面图
cover_prompt = result.get('coverPrompt', '')
if cover_prompt:
d4_score += 20
else:
d4_score += 10
scores['D4'] = min(100, d4_score)
# D5: 数据库写入正确性 (20%)
# JSON 格式规范性、必填字段完整性
d5_score = 0
# 必填字段检查
required_fields = ['name', 'title', 'language', 'characters', 'script']
field_count = sum(1 for f in required_fields if f in result and result[f])
d5_score += int(40 * (field_count / len(required_fields)))
# systemPrompt 检查
system_prompt = result.get('systemPrompt', '')
if len(system_prompt) >= 100:
d5_score += 30
elif len(system_prompt) >= 50:
d5_score += 20
elif system_prompt:
d5_score += 10
# tags 和 description 检查
tags = result.get('tags', '')
if tags and description:
d5_score += 30
elif tags or description:
d5_score += 15
scores['D5'] = min(100, d5_score)
# 计算总分
total = (scores['D1'] * 0.20 + scores['D2'] * 0.20 +
scores['D3'] * 0.20 + scores['D4'] * 0.20 +
scores['D5'] * 0.20)
# 评分等级
if total >= 95:
grade = 'A+'
elif total >= 85:
grade = 'A'
elif total >= 80:
grade = 'B+'
elif total >= 70:
grade = 'B'
elif total >= 60:
grade = 'C'
else:
grade = 'D'
result_output = {
"score": round(total, 2),
"grade": grade,
"dimensions": scores,
"breakdown": {
"D1_素材分析准确性": f"{scores['D1']} × 20% = {scores['D1'] * 0.20:.1f}",
"D2_角色配置合理性": f"{scores['D2']} × 20% = {scores['D2'] * 0.20:.1f}",
"D3_剧本结构完整性": f"{scores['D3']} × 20% = {scores['D3'] * 0.20:.1f}",
"D4_图片生成质量": f"{scores['D4']} × 20% = {scores['D4'] * 0.20:.1f}",
"D5_数据库写入正确性": f"{scores['D5']} × 20% = {scores['D5'] * 0.20:.1f}"
},
"reason": "基于 benchmark_v1.md 5维度评估",
"char_count": char_count,
"script_count": script_count
}
print(json.dumps(result_output, indent=2, ensure_ascii=False))
return result_output
if __name__ == '__main__':
result_file = '/tmp/result.json'
with open(result_file, 'r') as f:
result_json = f.read()
evaluate(result_json, '', '')